Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance their skills, public health awareness, and pharmacy inventory management, ensuring access to essential medicines that ultimately benefit their patients. We introduce a reinforcement learning operational system to deliver personalized behavioral interventions through mobile health applications. We illustrate its potential by discussing a series of initial experiments run with SwipeRx, an all-in-one app for pharmacists, including B2B e-commerce, in Indonesia. The proposed method has broader applications extending beyond pharmacy operations to optimize healthcare delivery.
@article{arxiv.2408.07647,
title = {Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services},
author = {Ana Fernández del Río and Michael Brennan Leong and Paulo Saraiva and Ivan Nazarov and Aditya Rastogi and Moiz Hassan and Dexian Tang and África Periáñez},
journal= {arXiv preprint arXiv:2408.07647},
year = {2024}
}
Comments
Presented at The First Workshop on AI Behavioral Science (AIBS'24) at KDD 2024, August 25, Barcelona, Spain